seqconfint | R Documentation |
Calculates the repeated confidence bound or the confidence bound based on the stage-wise ordering of a GSD or a AGSD
seqconfint(object, type = c("r", "so"), level = NULL)
object |
object of the |
type |
confidence type: repeated "r", stage-wise ordering "so" or both "b" (default: "b") |
level |
type I error rate (default: NULL) |
object
can be an object of the class
GSTobj
or an object of the class
AGSTobj
.
The function identifies the class
of the object and calculates the corresponding confidence interval (classical or adaptive).
If object
has class
GSTobj
, then a confidence bound for a classical GSD is calculated.
type
defines the type of confidence interval that is calculated
"r" | Repeated confidence bound for a classical GSD |
"so" | Confidence bound for a classical GSD based on the stage-wise ordering |
If object
has class
AGSTobj
, then a confidence bound for a GSD with design adaptation is calculated.
type
defines the type of confidence interval that is calculated
"r" | Repeated confidence bound for a GSD with design adaptations |
"so" | Confidence bound for a GSD with design adaptation based on the stage-wise ordering |
By setting level
to the value 0.5 the conservative point estimate is calculated. Default is the level
of the primary trial.
The function seqconfint
returns according to the class
of object
the classical or adaptive confidence bound.
If object
has class
GSTobj
the classical confidence bound is calculated. If the
parameter value has the class
AGSTobj
the adaptive confidence bound is calculated.
The calculated confidence bounds are saved as:
cb.r |
repeated confidence bound |
cb.so |
confidence bound based on the stage-wise ordering |
If the level
is set to 0.5, the calculated point estimates are:
est.mu |
Median unbiased point estimate, based on the stage-wise ordering |
est.cons |
Flexible, but conservative repeated point estimate |
The stage-wise adjusted confidence interval can only be calculated at the stage where the trial stops and is only valid if the stopping rule is met.
The repeated confidence interval can be calculated at every stage of the trial and not just at the stage where the trial stops and is also valid if the stopping rule is not met.
For calculating the sequential confidence intervals at stage T
the user has to specify the outcome GSDo
in the object GSTobj
or sTo
(secondary trial outcome) in the object AGSTobj
. A trial outcome is a list of the form
list=(T=stage of interim analysis, z = interim z-statistic)
; see the example below.
Niklas Hack niklas.hack@meduniwien.ac.at and Werner Brannath werner.brannath@meduniwien.ac.at
Brannath, W, Mehta, CR, Posch, M (2008) ”Exact confidence bounds following adaptive group sequential tests”, Biometrics accepted.
Jennison, C, Turnbull, BW (1989) ”Repeated confidence intervals for group sequential clinical trials”, Contr. Clin. Trials, 5, 33-45.
Mehta, CR, Bauer, P, Posch, M, Brannath, W (2007) ”Repeated confidence intervals for adaptive group sequential trials”, Statistics in Medicine, 26, 5422-5433.
Mueller, HH, Schaefer, H (2001) ”Adaptive group sequential design for clinical trials: Combining the advantages of adaptive and of classical group sequential approaches”, Biometrics, 57, 886-891.
Tsiatis,AA, Rosner,GL, Mehta,CR (1984) ”Exact confidence intervals following a group sequential test”, Biometrics, 40, 797-804.
AGSTobj
, GSTobj
##The following calculates the repeated confidence bound of a group sequential trial GSD <- plan.GST(K=4, SF=1, phi=0, alpha=0.025, delta=6, pow=0.8, compute.alab=TRUE, compute.als=TRUE) GST <- as.GST(GSD=GSD, GSDo=list(T=2, z=3.1)) seqconfint(GST, type="r") ##The confidence bound based on the stage-wise ordering of a group sequential trial is calculated by seqconfint(GST, type="so") ##The repeated confidence interval at the earlier stage T=1 where the ##trial stopping rule is not met. seqconfint(as.GST(GSD, GSDo=list(T=1, z=0.7)), type="r") ##The repeated confidence bound and the confidence bound ##based on the stage-wise ordering of a group sequential trial ##after a design adaptation is calculated by pT <- plan.GST(K=3, SF=4, phi=-4, alpha=0.05, delta=6, pow=0.9, compute.alab=TRUE, compute.als=TRUE) iD <- list(T=1, z=1.090728) swImax <- 0.0625 I2min <- 3*swImax I2max <- 3*swImax sT <- adapt(pT=pT, iD=iD, SF=1, phi=0, cp=0.8, theta=5, I2min, I2max, swImax) sTo <- list(T=2, z=2.393) AGST <- as.AGST(pT=pT, iD=iD, sT=sT, sTo=sTo) seqconfint(AGST) ##The repeated confidence interval at the earlier stage T=2 where the ##trial stopping rule is not met. seqconfint(as.AGST(pT, iD, sT, sTo=list(T=2, z=1.7)), type="r") ## Not run: ##If the stage-wise adjusted confidence interval is calculated at this stage, ##the function returns an error message seqconfint(as.AGST(pT, iD, sT, sTo=list(T=2, z=1.7)), type="so") ## End(Not run)
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